The study of the the low-molecular weight complement of cells, tissues, and biological fluids can be useful in assessing human health or the biochemical effects of exposures or pharmacological treatments on physiological systems. RTI is able to provide a well-established and uniquely broad range of experience and expertise with LC/MS-based analytical methods that are widely used in metabolomics research. With Dr. Jeremey Nicholson, Dr. Elaine Holmes, and Dr. Ian Wilson serving as co-investigators and consultants to the RCMRC, the proposed LC/MS-based metabolomics technology core will ensure that clients have access to the most recent methods available for data acquaition, analysis, and interpretation. Hence, the specific aims of the proposed LC/MS core are designed to leverage these critical capabilities to meet and exceed the requirements of the RCMRC and the service expectations of its scientific researchers. By integrating these capabilities and expertise with other cores, the LC/MS core at RTI will provide (1) consulting and educational outreach services; (2) the analytical capacity for the conduct of standardized LC/MS-based metabolomic methods and the development and inclusion of new methods and technology to meet the needs of ongoing and planned metabolomics studies, and (3) raw data and summary statistics in a manner consistent with the requirements ofthe DRCC and the needs ofthe client. Our LC/MS broad-spectrum metabolomics approach is designed to look at nonpolar and polar analytes using reverse phase and normal phase (HILIC) chromatographic methods coupled to time-of-flight mass spectrometry. Targeted metabolomic studies are supported on triple quadrupoles or Q-trap platforms with chromatographic conditions optimized for the target group of metabolites, and employ stable-isotope-dilution whenever possible. RTI is committed to providing a sustained infrastructure of staff, facilities, and instrumentation to support these efforts, and the RCMRC intends to continuously integrate the broad-spectrum metabolomics data with metabolite identification and peak matching data to generate a comprehensive reference database, and make it available as a resource to the metabolomics research community.